diff --git a/education/statistics/Hypothesis Tests.md b/education/statistics/Hypothesis Tests.md
index 6c8f59d..77d595d 100644
--- a/education/statistics/Hypothesis Tests.md	
+++ b/education/statistics/Hypothesis Tests.md	
@@ -12,7 +12,7 @@ If an observed value is too many SEs away from the expected value, it is hard to
 | Null Hypothesis | This is a statement about a *parameter*. It's a statement about equality. The chance of getting *x* is *y%*. A null hypothesis isn't proven true, you either prove it wrong (reject it), or don't (fail to reject).  |
 | Alternative/Research Hypothesis | What the researcher is out to prove, a statement of inequality. (Less than, greater than, not equal to). |
 | One-tailed test | Use when the alternative hypothesis says that the % of 1s is *less than* or *greater than* expected. It's one sided, because the area of importance on a distribution only has one side, and extends all the way outwards, away from the normal curve. |
-| Two tailed test | Use when something is *not equal* to the expected. It's called a two tailed test because the area of significance has two sides |
+| Two tailed test | Use when something is *not equal* to the expected. It's called a two tailed test because the area of significance has two sides. You can find the likelihood of ending up on one side, and the likelihood of ending up on another side, and adding them together (or multiplying by 2 if it's the same on each). |
 ## z tests for averages
 This test will look very similar to a z test for percentages, it still requires that a large, random, sample was given.
 ## P Value